1. Introduction

This is an R Markdown document that consolidates my exploratory data analysis (EDA) to understand the relationship between citizens’ participation and fiscal outcomes.

This study entailed the construction of a data set which combines local budget and fiscal performance data with available measures of local participation and other crucial covariates. The data set constructed leverages on the work already done by the World Bank (2021) and by C. Magno et al. (2022), mainly by enhancing the indicators on citizen participation.

This study adopts a panel regression model specified as follows:

y_hjt = D_jt’δ + X_ijt’β + u_jt

where y_hjt stands for budget performance measured by the hth metric of the jth Local Government Unit (LGU) in year t; D_jt is the vector of measures of participatory governance; X_ijt is the vector of covariates on the governance and socioeconomic characteristics of LGUs, grouped in i dimensions; and u_jt is the error term, decomposed further as the sum of α_j (LGU fixed effects) and ε_jt (idiosyncratic error).

The dependent variables y_hjt are metrics that illustrate the achievement of good public financial management (PFM): fiscal discipline, allocative efficiency, and operational efficiency. The explanatory variables D_jt are indicators that are available from the Seal of Good Local Governance (SGLG) on the participation of Civil Society Organizations (CSOs) in Local Development Councils (LDCs). The other covariates X_ijt are adapted from C. Magno et al. (2022) and include size of aggregate and functional budgets, LGU performance as measured by the SGLG, and socioeconomic development.

Based on the study’s empirical strategy, additional processing needed to be done in order to prepare the data for the regression analyses. First, only observations from 2017-2018, when all the CSO participation variables are present, will be included in the regression analyses. Second, extreme outliers and other defects in the dependent variables and one of the continuous explanatory variables (proportion of CSOs in the LDC) will be normalized through Winsorization at 98% (i.e., values below 1st percentile and above 99th percentile will be replaced with “NA”).ss

2. Exploration of the Variables

2.1 Outcome Variables (y_hjt)

The first outcome of good PFM is fiscal discipline, which pertains to the ability to keep government expenditure consistent with revenues. Typically, the fiscal deficit–the gap between revenues and disbursements, and the amount that needs to be borrowed to fill such gap–is used as the main metric of fiscal discipline. This is not applicable in the context of Philippine LGUs, which are enjoined by the LDC to maintain a balanced budget.

For the purpose of this study, metrics on the actual means of the LGUs will be used to measure performacne in this outcome area: (a) year on year growth of locally generated revenue and (b) dependence on fiscal transfers particularly the National Tax Allocation (NTA). On the former, annual growth of local revenues averaged 18% from 2017 to 2018. Although municipalities experienced the highest growth–an average of 19%%–cities continue to generate significantly higher revenues per capita compared to municipalities and provinces.

Summary of y1 = Annual Local Revenue Growth
Mean St Dev
City 0.1327 0.1638
Municipality 0.1912 0.3810
Province 0.1458 0.3758
All LGUs 0.1841 0.3676

Meanwhile, NTA dependence–which pertains to how LGUs rely on transfers from the national government rather than revenues they generate on their own–continued to be high at 80%. Municipalities and provinces are more NTA dependent at 82% and 80%, respectively, compared to 62% among cities which are more capable of generating revenues from real property, business, and other taxes. Cities and Municipalities are relatively on par when it comes the NTA they receive per capita, implying that Cities, which have higher per capita revenues, have more resources at their disposal.

Summary of y2 = NTA Dependence
Mean St Dev
City 0.6153 0.2424
Municipality 0.8177 0.1838
Province 0.7987 0.1253
All LGUs 0.7994 0.1955

The second PFM outcome–allocative efficiency–pertains to the ability of LGUs to allocate more resources to development priorities. While LGUs need to spend according to their unique local priorities, one could infer that it is better for LGUs to increase the share of productive expenditures, as opposed to overhead and other expenditures not for socioeconomic development.

There are two ways that one could measure productive expenditures. The first is the combined shares of budgets for maintenance and other operating expenditures (MOOE) and for capital outlays (CO) in the total budget. The remainder are budgets for personnel services (PS), debt servicing, and other unclassified items. Based on this definition, 60% of LGUs’ budgets, on average, are allocated for MOOE and CO, with provinces allocating largest shares of about 68%.

Summary of y3 = Share of Productive Expenditures (MOOE + CO)
Mean St Dev
City 0.6786 0.1211
Municipality 0.5917 0.1334
Province 0.6844 0.1043
All LGUs 0.6042 0.1346

The second way of calculating for productive expenditures is by sector and fund, specifically by excluding general public services (GPS) and other sectors from the total. This results in a lower share of productive expenditures at an average of 41%. Still, provinces continue to allocate larger shares to productive expenditures compared to municipalities.

Summary of y4 = Share of Productive Sectors in the Budget
Mean St Dev
City 0.4799 0.1467
Municipality 0.3986 0.1404
Province 0.5620 0.1305
All LGUs 0.4143 0.1464

Finally, operational efficiency pertains to the ability of LGUs to utilize resources effectively to deliver services. For this study, we use two indicators of operational efficiency: (a) per capita expenditures, which is a rough proxy for LGUs’ overall capability to deliver services, and (b) the budget utilization rate (BUR), which stands for the rate of actual expenditures against the approved budgets of LGUs.

LGUs per capita expenditures average PHP 3,274 annually. As expected, cities spend more per capita at PHP 4,742. Meanwhile, provinces spend the least per person at PHP 2,129. Growth in per capita expenditures also affects per capita productive spending, which averages PHP 1,301 annually.

Summary of y5 = Per Capita Expenditures
Mean St Dev
City 4879.380 2321.291
Municipality 3389.345 1998.605
Province 2048.815 1146.719
All LGUs 3448.757 2063.427
Summary of y5 = Per Capita Productive Expenditures
Mean St Dev
City 1942.054 1643.186
Municipality 1190.415 1751.053
Province 1169.895 1041.826
All LGUs 1253.274 1726.948

The budget utilization rate (BUR) has been the subject of the study by C. Magno et al. (2022). On average, LGUs utilize about 78% of their budgets. Cities tend to have lower BUR at 69%, while municipalities’ are higher at 79%. The overall BUR of LGUs have been decreasing. Finally, the LGUs’ utilization of their budgets for productive sectors is lower at 72%.

Summary of y6 = Budget Utilization Rate
Mean St Dev
City 0.6942 0.1680
Municipality 0.7882 0.1479
Province 0.7196 0.1443
All LGUs 0.7764 0.1525
Summary of y6 = Budget Utilization Rate
Mean St Dev
City 0.6817 0.1828
Municipality 0.7267 0.3035
Province 0.6772 0.1973
All LGUs 0.7202 0.2906

Note: with the behavior of the distributions of original data vs. log-transformed data, we select the former over the latter. Except in the case of NTA dependence, the original data are fairly normally distributed and the log transformation just retains the distribution or worsens any skewedness. The distribution of NTA dependence warrants an exploration of alternative distributions such as quasi-binomial or beta.

2.2 Explanatory Variables (D_jt)

Beginning 2017, measures on the functionality of LDCs have been added to the SGLG. These measures include whether the Council was organized and if CSO members of the council meet or exceed the 25% requirement of the LGC. C. Magno et al. (2022) found that the share of CSO members in the LDC did not have a statistically significant relationship with LGUs’ BUR. This thesis replicates the said analysis by relating CSO participation with other fiscal outcomes and making use of other variables available from the SGLG on CSO participation in LDCs:

  1. Whether or not the LGU met the minimum 25% of CSO members in the LDC

  2. Actual proportion of CSO members in the LDC

  3. Whether or not the LDC secretariat tapped the CSO (non-government organizations, research organizations and/or academic institutions) for technical support.

  4. Whether or not the CSO members participated in the LDC deliberations

  5. Whether or not the CSO members submitted a CSO plan to follow through on LDC deliberations

The indicators outlined above could be considered as measuring varying depths of CSO participation: from mere presence (where nearly all LGUs claim to have the minimum CSO representatives in the LDC) to a more meaningful engagement (where only in a minority of LGUs have CSOs submitted an action plan). Though the indicators do not reveal the substance or topics of the discussions, the quality of the action plans, or even the power dynamics between the local officials and the CSOs, these indicators are useful for now in illustrating the funnel of citizen participation.

Summary of SGLG Indicators on CSO Participation in LDCs
LDCs with Minimum CSO Members Mean % CSO Representation LDC Secretariats with CSO Support LDCs with CSOs Attending Meetings LDCs with CSOs Submitting Action Plans
City 0.8493 0.2811 0.4966 0.8390 0.1884
Municipality 0.7823 0.3038 0.4685 0.7634 0.1652
Province 0.9074 0.3133 0.5679 0.8642 0.1605
All LGUs 0.7939 0.3004 0.4756 0.7746 0.1670

In addition to participation in the LDC, the SGLG also has indicators on the participation of CSOs (a minimum of four representatives, plus minimum of one other member from the private sector) in the Local Risk Reduction and Management Councils (LDRRMCs). Under these shallow metrics, 84 percent of LGUs have met the minimum requirement.

Summary of SGLG Indicators on CSO Participation in LDRRMC
LDRRMCs with Minimum CSO Members LDRRMCs with Minimum Private Sector Member
City 0.8801 0.8870
Municipality 0.8325 0.8208
Province 0.9259 0.9259
All LGUs 0.8410 0.8314

It can be argued that meaningful participation cannot be achieved without proper mechanisms to access the information they need and to hold LGUs accountable.

On transparency, the SGLG tracks LGUs’ compliance with the Full Disclosure Policy (FDP) where LGUs are required to post financial and other reports physically in conspicuous places in the provincial, city, or municipal hall; and to submit the same in the FDP Portal. Compliance is high at about 90%.

Summary of SGLG Indicators on Full Disclosure
LGUs that Conspiculously Post their Financial Disclosures LGUs that Submit Financial Reports to the FDP Portal
City 0.9144 0.9075
Municipality 0.8942 0.8581
Province 0.9630 0.9444
All LGUs 0.8992 0.8664

Meanwhile, accountability is understood in many ways–from having strong oversight from the legislature and an independent audit office, to the ultimate accountability mechanism of the elections–but for the purpose of this study we use the audit rating provided by the Commission on Audit (COA) on the financial accounts of LGUs. As could be gleaned below, an overwhelming 88% of LGUs have qualified audit findings.

Summary of LGU Audit Ratings
Unqualified Qualified Disclaimer Adverse No Opinion or Report
City 0.0377 0.9041 0.0103 0.0411 0.0068
Municipality 0.0738 0.8804 0.0199 0.0108 0.0152
Province 0.1296 0.8519 0.0062 0.0000 0.0123
All LGUs 0.0734 0.8810 0.0184 0.0129 0.0143

3. Exploration of Relationships

The scatterplots shown below seem to imply no strong relationship between CSO participation measured as proportion of CSO members in the LDC and good budget performance. These are with the expception of the share of productive sectors and funds in the budget (slightly negative) and spending per capita (positive).

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

4. Statistical Summary Tables

Statistical Summary Table for All LGUs
Statistic N Mean St. Dev. Min Max
y1_locrevgrowth 3,351 0.18 0.37 -0.74 3.27
y2_ntadepend 3,388 0.80 0.20 0.00 1.00
y3_prodshare1 3,013 0.60 0.13 0.11 0.95
y3_mooeshare 3,013 0.40 0.12 0.01 0.77
y3_coshare 3,044 0.20 0.12 0.00 0.62
y4_prodshare2 3,044 0.41 0.15 0.00 0.93
y4_educshare 3,044 0.02 0.03 0.00 0.20
y4_healthshare 3,044 0.06 0.05 0.00 0.27
y4_socialshare 3,044 0.02 0.03 0.00 0.20
y4_econshare 3,044 0.08 0.08 0.00 0.58
y4_ldfshare 3,044 0.14 0.07 0.00 0.38
y4_ldrrmfshare 3,044 0.05 0.05 0.00 0.21
y5_spendpercap 3,036 3,448.76 2,063.43 2.02 17,964.14
y5_mooepercap 3,321 1,280.60 920.13 0.00 6,745.18
y5_copercap 3,321 408.76 494.88 0.00 3,876.04
y5_educpercap 3,321 50.98 99.52 0.00 1,028.30
y5_healthpercap 3,321 221.02 199.72 0.00 1,289.39
y5_socialpercap 3,321 81.51 107.12 0.00 796.59
y5_econpercap 3,321 219.91 251.83 0.00 2,046.84
y5_ldfpercap 3,321 317.58 321.42 0.00 2,245.49
y5_ldrrmfpercap 3,321 127.42 186.89 0.00 1,246.85
y6_bur 3,013 0.78 0.15 0.19 1.10
y6_bur_mooe 2,961 4.71 9.84 0.08 85.52
y6_bur_co 2,990 0.54 0.33 0.00 2.98
y6_bur_educ 2,050 0.73 0.25 0.00 1.58
y6_bur_health 2,506 0.88 0.12 0.10 1.13
y6_bur_social 2,675 0.85 0.19 0.00 1.19
y6_bur_econ 2,715 0.79 0.23 0.01 1.41
y6_bur_ldf 2,676 0.57 0.29 0.00 1.01
y6_bur_ldrrmf 2,594 0.59 0.35 0.00 2.37
log_y1_locrevgrowth 2,679 -1.85 1.13 -7.73 1.18
log_y2_ntadepend 3,388 -0.34 0.84 -6.91 -0.00
log_y3_prodshare1 3,013 -0.53 0.27 -2.19 -0.05
log_y3_mooeshare 3,013 -0.97 0.39 -4.70 -0.26
log_y3_coshare 3,044 -2.02 1.21 -6.91 -0.47
log_y4_prodshare2 3,044 -1.03 0.87 -6.91 -0.08
log_y4_educshare 3,044 -4.97 1.60 -6.91 -1.60
log_y4_healthshare 3,044 -3.40 1.68 -6.91 -1.30
log_y4_socialshare 3,044 -4.22 1.22 -6.91 -1.60
log_y4_econshare 3,044 -3.14 1.45 -6.91 -0.53
log_y4_ldfshare 3,044 -2.54 1.71 -6.91 -0.96
log_y4_ldrrmfshare 3,044 -3.79 1.60 -6.91 -1.54
log_y5_spendpercap 3,036 7.99 0.62 1.10 9.80
log_y5_mooepercap 3,321 6.42 2.17 0.00 8.82
log_y5_copercap 3,321 4.93 2.13 0.00 8.26
log_y5_educpercap 3,321 2.36 2.05 0.00 6.94
log_y5_healthpercap 3,321 4.17 2.43 0.00 7.16
log_y5_socialpercap 3,321 3.39 1.86 0.00 6.68
log_y5_econpercap 3,321 4.33 2.16 0.00 7.62
log_y5_ldfpercap 3,321 4.46 2.48 0.00 7.72
log_y5_ldrrmfpercap 3,321 3.31 2.26 0.00 7.13
log_y6_bur 3,013 -0.28 0.23 -1.66 0.10
log_y6_bur_mooe 2,961 0.70 1.13 -2.56 4.45
log_y6_bur_co 2,990 -0.95 1.18 -6.91 1.09
log_y6_bur_educ 2,050 -0.47 0.88 -6.91 0.46
log_y6_bur_health 2,506 -0.14 0.17 -2.28 0.12
log_y6_bur_social 2,675 -0.22 0.42 -5.18 0.18
log_y6_bur_econ 2,715 -0.32 0.50 -4.16 0.34
log_y6_bur_ldf 2,676 -0.89 1.27 -6.91 0.01
log_y6_bur_ldrrmf 2,594 -1.03 1.61 -6.91 0.86
ldc_cso25pct 3,430 0.79 0.40 0 1
ldc_csopct 3,037 0.31 0.08 0.13 0.85
ldc_csoattend 3,421 0.77 0.42 0 1
ldc_csoassist 3,421 0.48 0.50 0 1
ldc_csoplan 3,420 0.17 0.37 0 1
ldrrmc_cso4reps 3,422 0.84 0.37 0 1
fdp_posting 3,421 0.90 0.30 0 1
fdp_portal 3,421 0.87 0.34 0 1
coa_unqualified 3,421 0.07 0.26 0 1
coa_qualified 3,421 0.88 0.32 0 1
coa_disclaimer 3,421 0.02 0.13 0 1
coa_adverse 3,421 0.01 0.11 0 1
coa_noreptop 3,421 0.01 0.12 0 1
budget_percapita 3,355 5,202.77 12,728.24 0.00 400,698.00
log_gpsbudget 3,355 16.25 5.82 0.00 23.66
log_educbudget 3,355 9.31 7.48 0.00 22.08
log_healthbudget 3,355 12.51 7.08 0.00 22.27
log_socialbudget 3,355 12.34 6.00 0.00 21.85
log_econbudget 3,355 13.51 6.35 0.00 23.02
log_devfund 3,355 13.79 6.83 0.00 21.41
log_drrfund 3,355 12.33 6.65 0.00 21.08
log_psbudget 3,355 16.27 5.31 0.00 22.73
log_mooebudget 3,355 16.39 5.35 0.00 23.22
log_cobudget 3,355 15.40 5.36 0.00 22.99
log_debtbudget 3,355 6.66 7.67 0.00 21.28
laglog_budget 3,353 17.09 5.64 0.00 23.92
laglog_gpsbudget 3,353 15.89 6.08 0.00 23.66
laglog_educbudget 3,353 8.86 7.48 0.00 21.84
laglog_healthbudget 3,353 12.15 7.19 0.00 21.94
laglog_socialbudget 3,353 12.04 6.08 0.00 21.51
laglog_econbudget 3,353 13.26 6.40 0.00 22.91
laglog_devfund 3,353 12.90 7.31 0.00 21.06
laglog_drrfund 3,353 11.98 6.88 0.00 20.26
laglog_psbudget 3,353 15.98 5.56 0.00 22.73
laglog_mooebudget 3,353 16.09 5.58 0.00 22.97
laglog_cobudget 3,353 14.85 5.66 0.00 22.99
laglog_debtbudget 3,353 6.64 7.66 0.00 21.02
sglg_financial 3,430 0.28 0.45 0 1
sglg_disaster 3,430 0.25 0.44 0 1
sglg_social 3,430 0.27 0.45 0 1
sglg_eodb 3,430 0.69 0.46 0 1
sglg_peace 3,430 0.40 0.49 0 1
sglg_envi 3,430 0.57 0.50 0 1
sglg_culture 3,430 0.63 0.48 0 1
sglg_overall 3,430 0.19 0.39 0 1
pop_density_2018 3,430 776.20 3,045.19 0.65 72,798.68
poverty_2018 3,428 23.37 17.59 0.30 89.55
pop_urbanpct_2018 3,430 0.22 0.27 0.00 1.00
Statistical Summary Table for Municipalities
Statistic N Mean St. Dev. Min Max
y1_locrevgrowth 2,909 0.19 0.38 -0.74 3.27
y2_ntadepend 2,935 0.82 0.18 0.00 1.00
y3_prodshare1 2,592 0.59 0.13 0.11 0.95
y3_mooeshare 2,591 0.39 0.12 0.01 0.77
y3_coshare 2,618 0.19 0.12 0.00 0.62
y4_prodshare2 2,619 0.40 0.14 0.00 0.92
y4_educshare 2,624 0.02 0.03 0.00 0.20
y4_healthshare 2,640 0.06 0.04 0.00 0.27
y4_socialshare 2,628 0.03 0.03 0.00 0.20
y4_econshare 2,622 0.07 0.07 0.00 0.58
y4_ldfshare 2,620 0.14 0.07 0.00 0.38
y4_ldrrmfshare 2,619 0.05 0.05 0.00 0.21
y5_spendpercap 2,611 3,389.35 1,998.60 2.02 17,964.14
y5_mooepercap 2,879 1,202.27 845.67 0.00 6,745.18
y5_copercap 2,875 383.92 470.08 0.00 3,876.04
y5_educpercap 2,891 40.78 82.50 0.00 973.59
y5_healthpercap 2,888 200.04 178.82 0.00 1,233.61
y5_socialpercap 2,880 82.22 106.97 0.00 796.59
y5_econpercap 2,884 200.72 221.09 0.00 1,952.92
y5_ldfpercap 2,875 320.31 318.78 0.00 2,245.49
y5_ldrrmfpercap 2,877 131.11 192.11 0.00 1,246.85
y6_bur 2,591 0.79 0.15 0.19 1.10
y6_bur_mooe 2,540 5.10 10.49 0.08 85.52
y6_bur_co 2,568 0.55 0.34 0.00 2.98
y6_bur_educ 1,708 0.74 0.25 0.00 1.58
y6_bur_health 2,130 0.89 0.11 0.10 1.13
y6_bur_social 2,276 0.86 0.18 0.00 1.19
y6_bur_econ 2,309 0.81 0.22 0.01 1.41
y6_bur_ldf 2,310 0.58 0.29 0.00 1.01
y6_bur_ldrrmf 2,228 0.61 0.35 0.00 2.37
log_y1_locrevgrowth 2,317 -1.81 1.13 -7.73 1.18
log_y2_ntadepend 2,935 -0.31 0.84 -6.91 -0.00
log_y3_prodshare1 2,592 -0.55 0.27 -2.19 -0.05
log_y3_mooeshare 2,591 -0.99 0.40 -4.70 -0.26
log_y3_coshare 2,618 -2.09 1.24 -6.91 -0.47
log_y4_prodshare2 2,619 -1.08 0.92 -6.91 -0.08
log_y4_educshare 2,624 -5.11 1.53 -6.91 -1.60
log_y4_healthshare 2,640 -3.48 1.69 -6.91 -1.30
log_y4_socialshare 2,628 -4.20 1.23 -6.91 -1.60
log_y4_econshare 2,622 -3.24 1.46 -6.91 -0.54
log_y4_ldfshare 2,620 -2.50 1.70 -6.91 -0.96
log_y4_ldrrmfshare 2,619 -3.78 1.62 -6.91 -1.54
log_y5_spendpercap 2,611 7.98 0.62 1.10 9.80
log_y5_mooepercap 2,879 6.33 2.22 0.00 8.82
log_y5_copercap 2,875 4.84 2.16 0.00 8.26
log_y5_educpercap 2,891 2.21 1.98 0.00 6.88
log_y5_healthpercap 2,888 4.03 2.45 0.00 7.12
log_y5_socialpercap 2,880 3.38 1.90 0.00 6.68
log_y5_econpercap 2,884 4.22 2.20 0.00 7.58
log_y5_ldfpercap 2,875 4.47 2.49 0.00 7.72
log_y5_ldrrmfpercap 2,877 3.30 2.29 0.00 7.13
log_y6_bur 2,591 -0.26 0.22 -1.66 0.10
log_y6_bur_mooe 2,540 0.74 1.17 -2.56 4.45
log_y6_bur_co 2,568 -0.93 1.20 -6.91 1.09
log_y6_bur_educ 1,708 -0.46 0.93 -6.91 0.46
log_y6_bur_health 2,130 -0.12 0.17 -2.28 0.12
log_y6_bur_social 2,276 -0.19 0.39 -5.18 0.18
log_y6_bur_econ 2,309 -0.28 0.45 -4.16 0.34
log_y6_bur_ldf 2,310 -0.86 1.23 -6.91 0.01
log_y6_bur_ldrrmf 2,228 -1.01 1.62 -6.91 0.86
ldc_cso25pct 2,976 0.78 0.41 0 1
ldc_csopct 2,615 0.31 0.08 0.13 0.85
ldc_csoattend 2,967 0.76 0.43 0 1
ldc_csoassist 2,967 0.47 0.50 0 1
ldc_csoplan 2,966 0.17 0.37 0 1
ldrrmc_cso4reps 2,968 0.83 0.37 0 1
fdp_posting 2,967 0.89 0.31 0 1
fdp_portal 2,967 0.86 0.35 0 1
coa_unqualified 2,967 0.07 0.26 0 1
coa_qualified 2,967 0.88 0.32 0 1
coa_disclaimer 2,967 0.02 0.14 0 1
coa_adverse 2,967 0.01 0.10 0 1
coa_noreptop 2,967 0.02 0.12 0 1
budget_percapita 2,908 5,103.77 13,553.36 0.00 400,698.00
log_gpsbudget 2,908 15.84 5.85 0.00 22.52
log_educbudget 2,908 8.65 7.23 0.00 20.48
log_healthbudget 2,908 11.95 6.98 0.00 20.14
log_socialbudget 2,908 11.89 6.00 0.00 21.51
log_econbudget 2,908 12.93 6.31 0.00 22.73
log_devfund 2,908 13.50 6.72 0.00 21.25
log_drrfund 2,908 11.97 6.56 0.00 18.92
log_psbudget 2,908 15.88 5.34 0.00 22.73
log_mooebudget 2,908 15.95 5.34 0.00 22.52
log_cobudget 2,908 14.92 5.31 0.00 21.25
log_debtbudget 2,908 5.98 7.33 0.00 19.49
laglog_budget 2,907 16.66 5.65 0.00 22.74
laglog_gpsbudget 2,907 15.52 6.06 0.00 22.52
laglog_educbudget 2,907 8.25 7.21 0.00 20.02
laglog_healthbudget 2,907 11.62 7.07 0.00 20.71
laglog_socialbudget 2,907 11.62 6.05 0.00 21.51
laglog_econbudget 2,907 12.74 6.33 0.00 22.73
laglog_devfund 2,907 12.60 7.20 0.00 19.69
laglog_drrfund 2,907 11.65 6.79 0.00 18.57
laglog_psbudget 2,907 15.60 5.57 0.00 22.73
laglog_mooebudget 2,907 15.66 5.56 0.00 22.52
laglog_cobudget 2,907 14.37 5.60 0.00 20.13
laglog_debtbudget 2,907 5.99 7.32 0.00 19.49
sglg_financial 2,976 0.25 0.43 0 1
sglg_disaster 2,976 0.23 0.42 0 1
sglg_social 2,976 0.25 0.44 0 1
sglg_eodb 2,976 0.68 0.46 0 1
sglg_peace 2,976 0.37 0.48 0 1
sglg_envi 2,976 0.54 0.50 0 1
sglg_culture 2,976 0.60 0.49 0 1
sglg_overall 2,976 0.17 0.38 0 1
pop_density_2018 2,976 428.71 883.90 0.65 18,390.78
poverty_2018 2,974 24.81 17.87 1.46 89.55
pop_urbanpct_2018 2,976 0.17 0.23 0.00 1.00
Statistical Summary Table for Cities
Statistic N Mean St. Dev. Min Max
y1_locrevgrowth 287 0.13 0.16 -0.66 1.22
y2_ntadepend 291 0.62 0.24 0.00 0.96
y3_prodshare1 260 0.68 0.12 0.12 0.93
y3_mooeshare 262 0.43 0.13 0.10 0.76
y3_coshare 265 0.25 0.12 0.00 0.59
y4_prodshare2 263 0.48 0.15 0.00 0.93
y4_educshare 258 0.05 0.05 0.00 0.20
y4_healthshare 262 0.07 0.05 0.00 0.23
y4_socialshare 259 0.02 0.03 0.00 0.20
y4_econshare 263 0.13 0.12 0.00 0.57
y4_ldfshare 264 0.10 0.08 0.00 0.38
y4_ldrrmfshare 263 0.03 0.03 0.00 0.18
y5_spendpercap 265 4,879.38 2,321.29 120.21 16,677.86
y5_mooepercap 282 2,251.72 1,192.16 0.00 6,557.38
y5_copercap 284 697.52 668.47 0.00 3,490.43
y5_educpercap 268 169.95 181.20 0.00 1,028.30
y5_healthpercap 276 340.50 237.34 0.00 1,289.39
y5_socialpercap 279 87.90 99.11 0.00 622.88
y5_econpercap 279 416.10 399.70 0.00 2,046.84
y5_ldfpercap 285 344.30 380.05 0.00 2,138.66
y5_ldrrmfpercap 283 114.77 162.17 0.00 858.36
y6_bur 262 0.69 0.17 0.19 1.02
y6_bur_mooe 261 2.37 3.25 0.16 30.58
y6_bur_co 262 0.45 0.28 0.00 1.62
y6_bur_educ 219 0.66 0.24 0.00 1.20
y6_bur_health 241 0.81 0.13 0.23 1.10
y6_bur_social 241 0.75 0.22 0.01 1.15
y6_bur_econ 247 0.63 0.28 0.03 1.25
y6_bur_ldf 220 0.51 0.31 0.00 1.00
y6_bur_ldrrmf 218 0.49 0.32 0.00 1.33
log_y1_locrevgrowth 247 -2.09 0.91 -6.44 0.20
log_y2_ntadepend 291 -0.67 0.96 -6.91 -0.04
log_y3_prodshare1 260 -0.41 0.22 -2.11 -0.07
log_y3_mooeshare 262 -0.88 0.33 -2.27 -0.27
log_y3_coshare 265 -1.61 0.88 -6.91 -0.53
log_y4_prodshare2 263 -0.80 0.50 -6.91 -0.08
log_y4_educshare 258 -3.75 1.67 -6.91 -1.60
log_y4_healthshare 262 -3.04 1.24 -6.91 -1.47
log_y4_socialshare 259 -4.31 1.07 -6.91 -1.60
log_y4_econshare 263 -2.57 1.38 -6.91 -0.56
log_y4_ldfshare 264 -3.02 1.82 -6.91 -0.97
log_y4_ldrrmfshare 263 -4.08 1.45 -6.91 -1.72
log_y5_spendpercap 265 8.39 0.48 4.80 9.72
log_y5_mooepercap 282 7.16 2.02 0.00 8.79
log_y5_copercap 284 5.65 2.07 0.00 8.16
log_y5_educpercap 268 3.86 2.31 0.00 6.94
log_y5_healthpercap 276 5.01 2.12 0.00 7.16
log_y5_socialpercap 279 3.70 1.68 0.00 6.44
log_y5_econpercap 279 5.11 2.10 0.00 7.62
log_y5_ldfpercap 285 4.25 2.69 0.00 7.67
log_y5_ldrrmfpercap 283 3.29 2.22 0.00 6.76
log_y6_bur 262 -0.40 0.28 -1.64 0.02
log_y6_bur_mooe 261 0.45 0.83 -1.85 3.42
log_y6_bur_co 262 -1.14 1.14 -6.91 0.48
log_y6_bur_educ 219 -0.53 0.65 -6.91 0.19
log_y6_bur_health 241 -0.22 0.19 -1.45 0.10
log_y6_bur_social 241 -0.36 0.49 -4.35 0.14
log_y6_bur_econ 247 -0.62 0.67 -3.33 0.22
log_y6_bur_ldf 220 -1.24 1.72 -6.91 0.00
log_y6_bur_ldrrmf 218 -1.30 1.70 -6.91 0.28
ldc_cso25pct 292 0.85 0.36 0 1
ldc_csopct 267 0.30 0.06 0.20 0.67
ldc_csoattend 292 0.84 0.37 0 1
ldc_csoassist 292 0.50 0.50 0 1
ldc_csoplan 292 0.19 0.39 0 1
ldrrmc_cso4reps 292 0.88 0.33 0 1
fdp_posting 292 0.91 0.28 0 1
fdp_portal 292 0.91 0.29 0 1
coa_unqualified 292 0.04 0.19 0 1
coa_qualified 292 0.90 0.29 0 1
coa_disclaimer 292 0.01 0.10 0 1
coa_adverse 292 0.04 0.20 0 1
coa_noreptop 292 0.01 0.08 0 1
budget_percapita 285 7,286.09 4,610.54 0.00 44,385.67
log_gpsbudget 285 18.32 5.74 0.00 23.66
log_educbudget 285 13.88 7.67 0.00 22.08
log_healthbudget 285 15.76 6.46 0.00 22.27
log_socialbudget 285 14.61 5.95 0.00 21.85
log_econbudget 285 16.47 6.19 0.00 23.02
log_devfund 285 14.64 7.76 0.00 21.20
log_drrfund 285 13.58 7.31 0.00 21.08
log_psbudget 285 18.21 5.21 0.00 22.35
log_mooebudget 285 18.64 5.34 0.00 23.22
log_cobudget 285 17.89 5.42 0.00 22.99
log_debtbudget 285 10.89 8.43 0.00 21.28
laglog_budget 284 19.19 5.65 0.00 23.92
laglog_gpsbudget 284 17.51 6.62 0.00 23.66
laglog_educbudget 284 13.17 7.94 0.00 21.84
laglog_healthbudget 284 15.09 6.98 0.00 21.94
laglog_socialbudget 284 13.91 6.46 0.00 21.35
laglog_econbudget 284 15.75 6.76 0.00 22.91
laglog_devfund 284 13.55 8.31 0.00 20.83
laglog_drrfund 284 12.78 7.66 0.00 20.26
laglog_psbudget 284 17.82 5.62 0.00 22.30
laglog_mooebudget 284 18.28 5.64 0.00 22.97
laglog_cobudget 284 17.42 5.77 0.00 22.99
laglog_debtbudget 284 10.61 8.50 0.00 21.02
sglg_financial 292 0.48 0.50 0 1
sglg_disaster 292 0.44 0.50 0 1
sglg_social 292 0.43 0.50 0 1
sglg_eodb 292 0.79 0.41 0 1
sglg_peace 292 0.49 0.50 0 1
sglg_envi 292 0.74 0.44 0 1
sglg_culture 292 0.81 0.39 0 1
sglg_overall 292 0.33 0.47 0 1
pop_density_2018 292 4,565.02 9,242.16 120.24 72,798.68
poverty_2018 292 12.10 10.60 0.30 63.18
pop_urbanpct_2018 292 0.67 0.28 0.02 1.00
Statistical Summary Table for Provinces
Statistic N Mean St. Dev. Min Max
y1_locrevgrowth 155 0.15 0.38 -0.61 2.33
y2_ntadepend 162 0.80 0.13 0.22 0.98
y3_prodshare1 161 0.68 0.10 0.17 0.92
y3_mooeshare 160 0.44 0.11 0.11 0.75
y3_coshare 161 0.24 0.11 0.00 0.56
y4_prodshare2 162 0.56 0.13 0.21 0.89
y4_educshare 162 0.02 0.03 0.00 0.19
y4_healthshare 142 0.14 0.09 0.00 0.27
y4_socialshare 157 0.02 0.04 0.00 0.20
y4_econshare 159 0.12 0.12 0.00 0.58
y4_ldfshare 160 0.14 0.07 0.00 0.35
y4_ldrrmfshare 162 0.05 0.04 0.00 0.20
y5_spendpercap 160 2,048.81 1,146.72 625.33 7,089.11
y5_mooepercap 160 978.37 588.40 0.00 4,542.53
y5_copercap 162 343.29 397.17 0.00 2,760.02
y5_educpercap 162 36.04 44.06 0.00 249.31
y5_healthpercap 157 397.00 305.45 0.00 1,279.07
y5_socialpercap 162 57.71 120.00 0.00 689.99
y5_econpercap 158 223.93 292.28 0.00 1,936.25
y5_ldfpercap 161 221.65 226.52 0.00 1,912.40
y5_ldrrmfpercap 161 83.78 112.17 0.00 858.80
y6_bur 160 0.72 0.14 0.32 1.00
y6_bur_mooe 160 2.34 3.38 0.09 33.78
y6_bur_co 160 0.46 0.27 0.00 1.45
y6_bur_educ 123 0.66 0.24 0.09 1.39
y6_bur_health 135 0.83 0.12 0.36 1.00
y6_bur_social 158 0.75 0.23 0.02 1.02
y6_bur_econ 159 0.70 0.25 0.03 1.00
y6_bur_ldf 146 0.56 0.29 0.00 1.00
y6_bur_ldrrmf 148 0.55 0.35 0.00 2.18
log_y1_locrevgrowth 115 -2.13 1.50 -6.91 0.84
log_y2_ntadepend 162 -0.24 0.19 -1.52 -0.02
log_y3_prodshare1 161 -0.39 0.18 -1.77 -0.08
log_y3_mooeshare 160 -0.87 0.29 -2.16 -0.29
log_y3_coshare 161 -1.60 0.83 -6.91 -0.58
log_y4_prodshare2 162 -0.61 0.26 -1.56 -0.12
log_y4_educshare 162 -4.56 1.58 -6.91 -1.63
log_y4_healthshare 142 -2.69 1.89 -6.91 -1.30
log_y4_socialshare 157 -4.48 1.15 -6.91 -1.60
log_y4_econshare 159 -2.46 0.96 -6.91 -0.53
log_y4_ldfshare 160 -2.43 1.53 -6.91 -1.06
log_y4_ldrrmfshare 162 -3.49 1.30 -6.91 -1.63
log_y5_spendpercap 160 7.50 0.50 6.44 8.87
log_y5_mooepercap 160 6.72 0.74 0.00 8.42
log_y5_copercap 162 5.28 1.24 0.00 7.92
log_y5_educpercap 162 2.67 1.70 0.00 5.52
log_y5_healthpercap 157 5.15 2.10 0.00 7.15
log_y5_socialpercap 162 3.05 1.31 0.00 6.54
log_y5_econpercap 158 4.93 1.06 0.00 7.57
log_y5_ldfpercap 161 4.67 1.75 0.00 7.56
log_y5_ldrrmfpercap 161 3.49 1.69 0.00 6.76
log_y6_bur 160 -0.35 0.22 -1.13 0.00
log_y6_bur_mooe 160 0.44 0.82 -2.43 3.52
log_y6_bur_co 160 -1.04 0.89 -6.91 0.37
log_y6_bur_educ 123 -0.50 0.47 -2.36 0.33
log_y6_bur_health 135 -0.20 0.18 -1.03 0.00
log_y6_bur_social 158 -0.38 0.60 -4.02 0.02
log_y6_bur_econ 159 -0.47 0.59 -3.36 0.00
log_y6_bur_ldf 146 -0.87 1.09 -6.91 0.00
log_y6_bur_ldrrmf 148 -1.04 1.38 -6.91 0.78
ldc_cso25pct 162 0.91 0.29 0 1
ldc_csopct 155 0.31 0.09 0.15 0.82
ldc_csoattend 162 0.86 0.34 0 1
ldc_csoassist 162 0.57 0.50 0 1
ldc_csoplan 162 0.16 0.37 0 1
ldrrmc_cso4reps 162 0.93 0.26 0 1
fdp_posting 162 0.96 0.19 0 1
fdp_portal 162 0.94 0.23 0 1
coa_unqualified 162 0.13 0.34 0 1
coa_qualified 162 0.85 0.36 0 1
coa_disclaimer 162 0.01 0.08 0 1
coa_adverse 162 0.00 0.00 0 0
coa_noreptop 162 0.01 0.11 0 1
budget_percapita 162 3,314.61 3,049.95 789.15 25,808.05
log_gpsbudget 162 19.92 2.33 0.00 22.12
log_educbudget 162 13.29 7.61 0.00 20.66
log_healthbudget 162 16.87 6.75 0.00 21.17
log_socialbudget 162 16.45 2.96 0.00 20.99
log_econbudget 162 18.71 2.34 0.00 22.00
log_devfund 162 17.48 5.84 0.00 21.41
log_drrfund 162 16.63 5.02 0.00 20.11
log_psbudget 162 19.92 1.65 0.00 21.41
log_mooebudget 162 20.34 1.75 0.00 22.04
log_cobudget 162 19.55 2.40 0.00 21.70
log_debtbudget 162 11.39 8.29 0.00 19.87
laglog_budget 162 21.02 1.78 0.00 22.50
laglog_gpsbudget 162 19.68 2.78 0.00 22.11
laglog_educbudget 162 12.14 8.11 0.00 20.66
laglog_healthbudget 162 16.50 6.95 0.00 20.80
laglog_socialbudget 162 16.31 2.60 0.00 20.80
laglog_econbudget 162 18.26 3.11 0.00 21.51
laglog_devfund 162 17.33 5.78 0.00 21.06
laglog_drrfund 162 16.48 5.20 0.00 20.19
laglog_psbudget 162 19.58 2.75 0.00 21.25
laglog_mooebudget 162 19.96 2.83 0.00 21.93
laglog_cobudget 162 19.01 3.20 0.00 21.58
laglog_debtbudget 162 11.31 8.34 0.00 19.87
sglg_financial 162 0.36 0.48 0 1
sglg_disaster 162 0.33 0.47 0 1
sglg_social 162 0.35 0.48 0 1
sglg_eodb 162 0.68 0.47 0 1
sglg_peace 162 0.74 0.44 0 1
sglg_envi 162 0.83 0.38 0 1
sglg_culture 162 0.87 0.34 0 1
sglg_overall 162 0.21 0.41 0 1
pop_density_2018 162 330.31 458.15 27.16 2,672.49
poverty_2018 162 17.27 13.42 1.90 74.30
pop_urbanpct_2018 162 0.31 0.22 0.00 0.94
lgu_type n_lgus t_years N
All LGUs 1715 2 3430
City 146 2 292
Municipality 1488 2 2976
Province 81 2 162